Stochastic Models for Communications: Continuous-Time Stochastic Processes - Stationarity

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Stochastic Processes: Definitions and Examples

Covers stochastic processes in continuous time, including probability functions and stock processes.

Stochastic Processes for Communications: Continuous-Time Stationarity

Covers the concept of stationarity in continuous-time stochastic processes and its applications in communication systems.

Stochastic Models for Communications: Continuous-Time Stochastic Processes

Covers continuous-time stochastic processes and linear systems.

Continuous-Time Stochastic Processes: Linear System

Covers the analysis of continuous-time stochastic processes in the context of linear systems.

Introduction to Quantum Chaos

Covers the introduction to Quantum Chaos, classical chaos, sensitivity to initial conditions, ergodicity, and Lyapunov exponents.

Stochastic Models for Communications

Covers stochastic models for communications and the estimation of correlation functions.

Stochastic Models: Absorbing Markov Chains Examples

Covers examples of absorbing Markov chains in discrete time.

Wave Equations: Vibrating String

Explores the wave equation for a vibrating string and its numerical solution using finite difference formulas and the Newmark scheme in MATLAB/GNU Octave.

Queueing Theory: M/G/1 Queue

Covers the M/G/1 queue in stochastic models for communications, analyzing system performance metrics and steady-state analysis.

Quantum Eigenfunctions

Covers quantum eigenfunctions and the importance of A and B commuting for the same set of eigenfunctions.